{"id":"W4230753584","doi":"10.32920/ryerson.14639748","title":"Heterogeneous Human Capital and Migration: Who Migrates from Mexico to the US?","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Migration and Labor Dynamics","field":"Social Sciences","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Human capital; Emigration; Immigration; Download; Imperfect; Altruism (biology); Distribution (mathematics); Economics; Transferability; Government (linguistics); Demographic economics; Overlapping generations model; Capital (architecture); Labour economics; Political science; Geography; Economic growth; Psychology; Social psychology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005430968,0.0001491343,0.0002619627,0.0006260053,0.0009837478,0.001567636,0.0002190522,0.0004819209,0.00325292],"category_scores_gemma":[0.002338863,0.0000772446,0.0002017057,0.001246673,0.000672505,0.0008635877,0.0007765131,0.0005563879,0.0001506521],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000912582,"about_ca_system_score_gemma":0.0005790443,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05871691,"about_ca_topic_score_gemma":0.05380944,"domain_scores_codex":[0.9997985,0.00006063724,0.00000586156,0.00003870818,0.00001277169,0.00008359086],"domain_scores_gemma":[0.9991196,0.0002452405,0.0003935214,0.00005486242,0.0000469256,0.000139863],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003052173,0.0001636623,0.9311585,0.00006400661,0.000171495,0.0006498643,0.003708337,0.003787647,0.0003112505,0.01927535,0.003090164,0.03731436],"study_design_scores_gemma":[0.00005340104,0.0001189925,0.9485086,0.0002142301,0.0001756073,0.0002647579,0.01898218,0.005390144,0.0002787409,0.01462102,0.01135399,0.00003831319],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9906464,0.001010319,0.0005455459,0.004214706,0.00003274362,0.000007318969,0.0001968428,0.00000666359,0.003339557],"genre_scores_gemma":[0.9980773,0.0005732023,0.00013624,0.0001872532,0.00002221428,0.000005061345,0.00008488588,0.000002053048,0.0009117553],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05871691,"threshold_uncertainty_score":0.1167503,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01752167629015645,"score_gpt":0.2901839978965176,"score_spread":0.2726623216063612,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}